class_docstr: >>> Backbone()  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
  Backbone(
    (l1): Linear(...)
    (l2): Linear(...)
  )
code: def __init__(self, hidden_dim=128):
      super().__init__()
      self.l1 = torch.nn.Linear(28 * 28, hidden_dim)
      self.l2 = torch.nn.Linear(hidden_dim, 10)
  
imports: from os import path
  from typing import Optional
  import torch
  from lightning.pytorch import LightningDataModule, LightningModule, cli_lightning_logo
  from lightning.pytorch.cli import LightningCLI
  from lightning.pytorch.demos.mnist_datamodule import MNIST
  from lightning.pytorch.utilities.imports import _TORCHVISION_AVAILABLE
  from torch.nn import functional
  from torch.utils.data import DataLoader, random_split
label_desc: Use image node_id 1 to create a new Backbone object from inherited base classes: torch.nn with example: obj = Backbone(hidden_dim)